ASAP-MS combined with mass spectrum similarity and binary code for rapid and intelligent authentication of 78 edible flowers
文献类型：期刊论文
| 作者 | Meng, Qian2,3; Zhang, Jianqing3; Li, Xiaolan3; Li, Yun3; Shen, Xuanjing3; Li, Ziqing3; Xu, Meng3; Yao, Changliang3; Chu, Pengfei1; Cui, Ya-Jun2 |
| 刊名 | FOOD CHEMISTRY
 |
| 出版日期 | 2024-03-15 |
| 卷号 | 436页码:10 |
| ISSN号 | 0308-8146 |
| 关键词 | ASAP Flowers MATLAB Authentication |
| DOI | 10.1016/j.foodchem.2023.137776 |
| 通讯作者 | Cui, Ya-Jun(janney808@sina.com) ; Guo, De-an(daguo@simm.ac.cn) |
| 英文摘要 | This is the first report to use Atmospheric Pressure Solids Analysis Probe (ASAP) for rapid and intelligent authentication of 78 edible flowers. Mass spectra of 451 batches were collected, with each run for 1-2 min. Experimental raw data was automatically extracted and aligned to create a MS database, based on which flowers were identified by MS similarity scores and rankings. To avoid background interference, top 25 ions of each flower were screened and gathered into an m/z pool containing 292 ions (+) and 399 ions (-). Binary sequence IDs were then generated by automatically assigning "1 '' for presence and "0 '' for absence, resulting in 78 binary codes. Binary code similarity with 78 IDs was used for authentication. Above two approaches were automatically performed by MATLAB, and compared to k-nearest neighbor model, and samples were all successfully identified (100 %). The proposed method provides a high-throughput authentication approach for large-scale food samples. |
| WOS关键词 | SPECTROMETRY ; QUALITY |
| 资助项目 | National Natural Science Foundation of China[82003940] ; Qi-Huang Chief Scientist Project of National Administration of Traditional Chinese Medicine (2020) ; Shanghai Sailing Program[21YF1455800] ; Science and Technology Major Project of Inner Mongolia[2021ZD0017] |
| WOS研究方向 | Chemistry ; Food Science & Technology ; Nutrition & Dietetics |
| 语种 | 英语 |
| 出版者 | ELSEVIER SCI LTD |
| WOS记录号 | WOS:001098575100001 |
| 源URL | [http://119.78.100.183/handle/2S10ELR8/307854]  |
| 专题 | 中国科学院上海药物研究所 |
| 通讯作者 | Cui, Ya-Jun; Guo, De-an |
| 作者单位 | 1.Waters Technol Shanghai Co Ltd, Shanghai 201203, Peoples R China 2.Shanghai Univ Tradit Chinese Med, Cailun Rd 1200, Shanghai 201203, Peoples R China 3.Chinese Acad Sci, Shanghai Inst Mat Med, Natl Engn Res Ctr TCM Standardizat Technol, Haike Rd 501, Shanghai 201203, Peoples R China |
| 推荐引用方式 GB/T 7714 | Meng, Qian,Zhang, Jianqing,Li, Xiaolan,et al. ASAP-MS combined with mass spectrum similarity and binary code for rapid and intelligent authentication of 78 edible flowers[J]. FOOD CHEMISTRY,2024,436:10. |
| APA | Meng, Qian.,Zhang, Jianqing.,Li, Xiaolan.,Li, Yun.,Shen, Xuanjing.,...&Guo, De-an.(2024).ASAP-MS combined with mass spectrum similarity and binary code for rapid and intelligent authentication of 78 edible flowers.FOOD CHEMISTRY,436,10. |
| MLA | Meng, Qian,et al."ASAP-MS combined with mass spectrum similarity and binary code for rapid and intelligent authentication of 78 edible flowers".FOOD CHEMISTRY 436(2024):10. |
入库方式： OAI收割
来源：上海药物研究所
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